ex23
This model is a fine-tuned version of Qwen/Qwen2.5-Coder-0.5B-Instruct on the arm_opt_0, the arm_opt_1 and the arm_opt_2 datasets. It achieves the following results on the evaluation set:
- Loss: 0.0171
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 2
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0336 | 0.9362 | 61000 | 0.0237 |
| 0.0206 | 1.8725 | 122000 | 0.0172 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for ahmedheakl/ex23
Base model
Qwen/Qwen2.5-0.5B
Finetuned
Qwen/Qwen2.5-Coder-0.5B
Finetuned
Qwen/Qwen2.5-Coder-0.5B-Instruct